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NVH CAE is considered as one of the aspects of engine component design process. Following the best practices for CAE throughout the industry is the current trend which tend to miss the fact of improving it as per the continuously evolving component designs. Continuous improvement is necessary in existing methods and procedures to enhance CAE methodologies. Correlation of CAE models with measurement results increases stakeholders’ confidence and further allows to try out various combinations to reduce product development cycle time as well as cost. Engine components are connected with each other at periphery through bolted connection with required torque. The existing global CAE modeling practices are evolved to represent the bolt connections at the designed location. However, these practices miss the stiffness offered by the interface zone between bolts.

NVH predictions have gained importance since last few decades due to increased focus on ride comfort as competitive advantage within cost target. Hence, NVH CAE has become integral part of product development process for early issue identification and solutions. To make NVH simulation robust, continuous improvement is required in existing CAE processes. In automobile powertrains, components are connected with each other through fasteners. Gaskets are sandwiched at periphery between two mating components, while the components are bolted together with required torque. Gaskets are used to prevent leakage of oil and gases into the atmosphere while operation. NVH CAE modeling practices globally are evolved with considering gaskets as one of the less important modelled components. However, these practices miss to consider its effects considerably on NVH performance.

In research and development of any automotive industry the main challenge is to virtually simulate probable failures rather than relying on physical testing which consumes time and resources. It is even more challenging when it comes to failure prediction of ABS plastic parts due to its complexity in material, behavior and assembly variations. ABS material is used extensively in automotive vehicles especially in motorcycles and scooters due to its visual and structural benefits at moderate cost. In this paper, the work showcases a methodology to predict failure of ABS parts. In order to do so, understanding the shortcomings in the current system is necessary. With the help of testing database history of various vehicles on proving grounds, root causes and drawback with respect to current simulation process are identified for failure of ABS parts. The input excitations from proving ground are probabilistic, thus, random vibration fatigue process is then introduced to calculate life.

Process Parameters play a vital role in product quality of Injection Molded components. Variation in process parameters will lead to Injection Molded manufacturing defects like Sink Mark, Flow Mark, Silver Streak, Flash, Warping, Weld lines, Jetting, voids, Short Shot & Bubbles. This manuscript is innovative because suppliers (Tier 1 and Tier 2) do not use DoE for standardization of their process parameters in Injection Molding and High Pressure Die Casting. They do trial and error method to arrive at the process parameters which is error prone and time consuming. The variation of process parameters can be optimized using Six Sigma approach, a structured methodology which is Process focused & data driven approach.